diff --git a/pyeit/eit/fem.py b/pyeit/eit/fem.py
index 4c28c70..766f12b 100644
--- a/pyeit/eit/fem.py
+++ b/pyeit/eit/fem.py
@@ -54,7 +54,7 @@ def __init__(self, mesh, el_pos):
         self.n_tri, self.n_vertices = self.tri.shape
         self.ne = el_pos.size
 
-    def solve_eit(self, ex_mat=None, step=1, perm=None, parser=None):
+    def solve_eit(self, ex_mat=None, step=1, perm=None, parser="std"):
         """
         EIT simulation, generate perturbation matrix and forward v
 
@@ -98,7 +98,7 @@ def solve_eit(self, ex_mat=None, step=1, perm=None, parser=None):
         for i in range(n_lines):
             # FEM solver of one stimulation pattern, a row in ex_mat
             ex_line = ex_mat[i]
-            f, jac_i = self.solve(ex_line, perm0)
+            f, jac_i = self.solve(ex_line, perm0, parser=parser)
             f_el = f[self.el_pos]
 
             # boundary measurements, subtract_row-voltages on electrodes
@@ -122,7 +122,7 @@ def solve_eit(self, ex_mat=None, step=1, perm=None, parser=None):
         p = pde_result(jac=np.vstack(jac), v=np.hstack(v), b_matrix=np.vstack(b_matrix))
         return p
 
-    def solve(self, ex_line, perm):
+    def solve(self, ex_line, perm, parser):
         """
         with one pos (A), neg(B) driven pairs, calculate and
         compute the potential distribution (complex-valued)
@@ -156,7 +156,10 @@ def solve(self, ex_line, perm):
         r_el = r_matrix[self.el_pos]
 
         # 4. solving nodes potential using boundary conditions
-        b = self._natural_boundary(ex_line)
+        if parser == "mit_16c":
+            b = self._natural_boundary_mit(ex_line)
+        else:
+            b = self._natural_boundary(ex_line)
         f = np.dot(r_matrix, b).ravel()
 
         # 5. build Jacobian matrix column wise (element wise)
@@ -185,6 +188,14 @@ def _natural_boundary(self, ex_line):
 
         return b
 
+    def _natural_boundary_mit(self, ex_line):
+        """MIT has only one drive coil"""
+        drv_coil = self.el_pos[ex_line]
+        b = np.zeros((self.n_pts, 1))
+        b[drv_coil] = 1.0
+
+        return b
+
 
 def smear(f, fb, pairs):
     """
@@ -266,28 +277,34 @@ def voltage_meter(ex_line, n_el=16, step=1, parser=None):
         start from the positive stimulus electrodestart index 'A'.
         if parser is 'std', or 'no_rotate_meas' then data are trimmed,
         the start index (i) of boundary voltage measurements is always 0.
+        mit_16c : mit mode of 16 coils.
 
     Returns
     -------
     v: NDArray
         (N-1)*2 arrays of subtract_row pairs
     """
-    # local node
-    drv_a = ex_line[0]
-    drv_b = ex_line[1]
-    i0 = drv_a if parser in ("fmmu", "rotate_meas") else 0
-
-    # build differential pairs
-    v = []
-    for a in range(i0, i0 + n_el):
-        m = a % n_el
-        n = (m + step) % n_el
-        # if any of the electrodes is the stimulation electrodes
-        if not (m == drv_a or m == drv_b or n == drv_a or n == drv_b):
-            # the order of m, n matters
-            v.append([n, m])
-
-    diff_pairs = np.array(v)
+    if parser == "mit_16c":
+        diff = [[m, ex_line] for m in range(n_el) if m != ex_line]
+        diff_pairs = np.array(diff)
+    else:
+        # local node
+        drv_a = ex_line[0]
+        drv_b = ex_line[1]
+        i0 = drv_a if parser in ("fmmu", "rotate_meas") else 0
+
+        # build differential pairs
+        v = []
+        for a in range(i0, i0 + n_el):
+            m = a % n_el
+            n = (m + step) % n_el
+            # if any of the electrodes is the stimulation electrodes
+            if not (m == drv_a or m == drv_b or n == drv_a or n == drv_b):
+                # the order of m, n matters
+                v.append([n, m])
+
+        diff_pairs = np.array(v)
+
     return diff_pairs